Impact of body mass index at diagnosis on outcomes of pediatric acute leukemia: A systematic review and meta-analysis

Background The incidence of childhood malnutrition i.e., both obesity and undernutrition, is on a rise. While there is extensive evidence of the influence of body mass index (BMI) on the survival and other important outcomes of adult cancers, the impact of childhood BMI on one of the common pediatric cancers i.e., leukemia is not well studied. Methods Systematic search of PubMed, Scopus, and Google Scholar databases was done to identify studies that were conducted among pediatric patients with leukemia and had examined outcomes of interest based on BMI at the time of diagnosis. Results Effect sizes were reported as pooled hazards ratio (HR) along with 95% confidence intervals (CI). A total of 17 studies were included. Compared to pediatric leukemia patients with normal BMI, underweight (HR 1.07, 95% CI: 1.04, 1.11) and obese (HR 1.42, 95% CI: 1.18, 1.71) children with leukemia had higher risks of overall mortality. Underweight (HR 1.10, 95% CI: 1.02, 1.19) and obese (HR 1.34, 95% CI: 1.15, 1.55) pediatric leukemia patients had a tendency to lower event-free survival compared to children with normal BMI. The risk of relapse was not significant for underweight, overweight, and obese children. Conclusions Both underweight and obese status at the time of diagnosis were associated with poor survival outcomes in pediatric patients with leukemia.


Introduction
The incidence of childhood obesity is on the rise in the developed countries [1].Concurrently, in many of the countries, there is a dual burden of childhood undernutrition as well as obesity [2][3][4].According to a recent global estimate, around 40 million children under five years of age are either overweight or obese [5].On the other hand, around 45-50 million children, particularly from low-and middle-income countries suffer from wasting due to severe undernutrition [6,7].
Leukemia is one of the most prevalent childhood cancers, and one of the leading causes of cancer-related deaths among children [8][9][10].Acute lymphoblastic leukaemia (ALL) accounts for around three-fourth of all pediatric leukemia cases and is currently associated with significantly improved prognosis (5-year survival of around 80-85%) [11,12].
Malnutrition i.e., both under and over-nutrition, has been shown to influence the outcomes in adult cancers.Obesity, for instance, has been shown to influence the survival and relapse of some adult cancers [13][14][15].A credible body of evidence suggests a link between cancer prognosis and inflammation due to obesity.Adiposity that results from obesity creates a proinflammatory environment that could possibly contribute to adverse prognostic outcomes [16].Obesity is associated with an increased circulating levels of inflammatory cytokines such as interleukin-6 (IL-6) and tumour necrosis factor-alpha (TNFα) that may trigger an increase in the number of cells that have tumour-forming potential [16,17].On the other hand, studies demonstrate that undernutrition is associated with increased tumour aggressiveness, thereby, increasing the risk of recurrence and metastasis [17,18].Also, some evidence from certain adult cancers suggests that undernutrition may be associated with sub-optimal response to chemotherapy and associated side effects [19,20].
While there is evidence of the impact of body mass index (BMI) on the outcomes of certain cancers such as bladder cancer, colon cancer, nasopharyngeal cancer etc, the impact of childhood BMI on leukemia is unclear.Two prior systematic reviews on this issue have been published [21,22].One review by Amankwah et al. pooled 11 studies and documented that pediatric patients with high BMI were at increased risk of mortality [21].Similar review by Orgel et al was published in the year 2016 and demonstrated that high BMI correlated with increased risk of poor event free survival (EFS) and overall survival in children with both ALL and acute myelogenous leukemia (AML) [22].However, both these reviews were conducted nearly half a decade ago and with the new studies on this issue being published, there is a need to update the evidence.
This study aims to assess the impact of malnutrition status on the outcomes of pediatric patients with leukemia.

Search strategy, selection criteria and relevant methods
The PRISMA guidelines were followed for conducting this meta-analysis [23].The study was registered at PROSPERO, with the number: CRD42024497221.A systematic search was conducted using structured strategy (S1 Table ) across PubMed, Scopus and Google Scholar databases.This search aimed to identify English-language studies published until 15 th December 2023 that examined the association between body mass index (BMI) at the time of diagnosis with overall survival, event free survival (EFS), and relapse rate in pediatric patients with leukemia.
After executing the search strategy, and deduplication, two study authors independently reviewed titles and abstracts to identify potentially relevant studies.Full texts of the studies were then read to finally select the studies for the meta-analysis.If any disagreements arose, the two authors of the study reached a shared consensus through discussion.
Eligible studies should have examined pediatric patients with confirmed leukemia diagnosis and assessed relevant outcomes based on BMI at the time of diagnosis.Standardized BMI cutoffs for pediatric populations are not universally agreed upon, and variations exist in defining categories such as underweight, normal weight, overweight, and obesity.We made a decision to combine studies with different BMI cut-offs to maximize the available data, enhance statistical power, and acknowledge the variability in BMI categorization methods across the literature.We aimed to include observational studies (either with cohort, cross-sectional or casecontrol design).All included studies should have reported data of the control group of pediatric leukemia patients with normal BMI.
Case reports or reviews were excluded.Also, studies that did not compare outcomes of interest based on BMI at the time of diagnosis or the outcomes reported were not relevant for this meta-analysis were excluded.
A pilot-tested data extraction sheet was employed for the extraction process.Two study authors independently gathered required data from the included studies.All disagreements were resolved by consensus.The assessment of the included studies was conducted using the Newcastle-Ottawa Quality Assessment Scale for non-randomised studies [24].

Statistical analysis
All the analyses were done using STATA version 16.0.The effect sizes were reported as pooled hazards ratio (HR) along with 95% confidence intervals (CI).Pooled effect sizes were presented for underweight, overweight, and obese categories, compared to normal BMI at the time of diagnosis.A subgroup analysis was conducted based on diagnosis of acute lymphoblastic leukemia (ALL) or acute myeloid leukemia (AML).We used I 2 to report and assess the magnitude of heterogeneity.Random effects model was used in instances where I 2 was more than 40% [25].A P-value of less than 0.05 was considered statistically significant.Publication bias was also assessed using the Egger's test.
Of these, 11 were prospective cohort studies and 6 were retrospective data analyses.Seven studies were conducted in the USA.One study each was conducted in Mexico, Canada, United Kingdom, Brazil, China and Thailand.Finally, four multi-centre studies were included.Ten studies investigated pediatric acute lymphoblastic leukemia (ALL) patients, five investigated pediatric myeloid leukemia (AML) patients, and two investigated a mixed cohort, including patients with ALL, AML, chronic myeloid leukemia, or myelodysplastic syndrome) (Table 1).The quality of the included studies was judged to be good (Table 1).
BMI was the primary exposure.Included studies differed in the BMI cut-offs adopted for defining underweight, normal and obese children.Specific criteria used by the individual studies have been presented in Table 1.The different criteria were comprised of guidelines by the International Obesity Task Force (n = 1 study), z-score based approach (n = 1 study), BMI percentile-based approach (n = 12 studies) and use of WHO/CDC criteria (n = 3 studies).The variability in the cut-offs for categorizing underweight, normal, overweight and obese children was detected even in studies that used the percentile-based approach.
We noted that for the comparison between underweight and normal BMI children, around 95% of the weight was given to the study by Eissa et al (2017) [29].Therefore, we repeated the analysis after excluding this study.Our findings still indicated an increased risk of mortality (HR 1.17, 95% CI: 1.01, 1.   Egger's test did not detect the presence of publication bias (P = 0.40 for underweight category; P = 0.27 for overweight category; P = 0.64 for obese category).Subgroup analysis showed that underweight [ALL: HR 1.07, 95% CI: 1.02, 1.11; AML: HR 1.28, 95% CI: 1.03, 1.55] and obese [ALL: HR 1.67, 95% CI: 1.11, 2.55; AML: HR 1.41, 95% CI: 1.07, 1.83] children with ALL and AML both showed elevated risk of mortality compared to children with normal BMI (S2 Table ).
For analysis related to underweight children, around 60% of the weight was allocated to study by Eissa et al (2017) [29].We did a re-analysis after excluding this study and noted that the association with EFS was not statistically significant (HR 1.07, 95% CI: 0.94, 1.21;I 2 = 7.9%, N = 10) (S2 Fig) .Similarly, we found that for the comparison between overweight and normal BMI children, around 45% of the weight was given to the study by Eissa et al.On doing a sensitivity analysis after excluding this study, no statistical difference was found in the risk of event free mortality in overweight children (HR 1.12, 95% CI: 0.95, 1.32;I 2 = 20.9%,N = 6) (S2 Fig) .Subgroup analysis showed that underweight [ALL: HR 1.13, 95% CI: 1.05, 1.24; AML: HR 1.16, 95% CI: 1.03, 1.37] and obese [ALL: HR 1.62, 95% CI: 1.20, 2.23; AML: HR 1.35, 95% CI: 1.14, 1.56] children with ALL and AML both showed lower EFS rates compared to children with normal BMI (S2 Table ).
We did not find evidence of publication bias (P = 0.20 for underweight category; P = 0.31 for overweight category; P = 0.77 for obese category).Subgroup analysis showed that underweight, overweight, and obese children with ALL or AML were not at an increased risk of relapse, compared to children with normal BMI (S2 Table ).

Discussion
Our review found that underweight or obese pediatric leukemia patients had higher risk of mortality and poor EFS compared to children with normal BMI.There was no increased risk of mortality or poor EFS among patients who were overweight.Subgroup analysis showed that this effect of underweight and obese status on the risk of mortality and EFS was detected in both ALL and AML patients.Our results emonstrated that the risk of relapse was statistically similar across all BMI categories (underweight, overweight and obese), when compared to normal BMI.Our findings are similar to the earlier two reviews that also noted that higher BMI is associated with increased risk of mortality and lower EFS [21,22].However, earlier reviews did not clarify the operational definition of "higher BMI" and had variability in comparison groups among different included studies.For some, the comparator was normal BMI, while for others it was a combination of normal and underweight BMI.Further, previous reviews  did not consider other BMI categories as a "exposure of interest".In contrast, current metaanalysis showed that both high BMI (i.e., obesity) and underweight status were risk factors for poor outcomes.
The observed association of obesity with poor outcomes may be explained by several mechanisms.Obesity may impact pharmacokinetics and/or pharmacodynamics of the chemotherapeutic drugs, particularly those that are lipophilic [43,44].This may, in turn, affect the efficacy of these drugs and consequently, the outcomes.Obese children with ALL are likely to be at higher risk for treatment-related toxicities, such as steroid-induced hyperglycemia, asparaginase-induced pancreatitis, hepatic steatosis and osteonecrosis [45,46].This can easily limit the effective administration of chemotherapy and can force dose reductions.All these factors might contribute towards decreasing the probability of survival and/or EFS in children with high BMI.Also, obesity leads to a stage of chronic inflammation that may provide conducive milieu for tumour growth [47,48].Childhood obesity has been shown to be associated with quite a few comorbid conditions which may further reduce the quality of life [49].
Prior studies have indicated that underweight patients are at increased risk of cancer recurrence and that underweight status increases the risk of mortality in cancer patients due to infection and associated sepsis [17,50,51].We did not test the possibility of increased risk of infection and sepsis in underweight children but do believe that future studies should explore the BMI-infection-mortality pathway in pediatric cancer patients.Studies have also shown that there may be an increased risk of recurrence and metastasis in patients who are undernourished due to the increased tumour aggressiveness [17,18].Underweight children may experience compromised immune function and reduced physiological reserves, making them more susceptible to the adverse effects of aggressive cancer treatments.There have been suggestions that sub-optimal nutritional status might lead to an increased toxicity and possibly, a decreased response to chemotherapy [19,20].
Both underweight and obese children may experience delays in diagnosis and initiation of treatment.Underweight children might be more vulnerable to delayed diagnosis due to atypical or less noticeable symptoms, while obesity may contribute to diagnostic challenges, masking symptoms or complicating the interpretation of laboratory results.Psychosocial factors might also play a role.Underweight children may face socioeconomic disparities and limited access to healthcare, impacting timely diagnosis and intervention.On the other hand, obese children might encounter stigma or bias in healthcare settings, potentially influencing the quality of care they receive.
We do acknowledge that there are certain limitations of this review.A noteworthy limitation is that most studies were retrospective and therefore, it is possible that some of the important variables or confounders were not adjusted in the analysis.This may make the reported effect sizes in individual studies biased.Majority of the studies failed to comprehensively report on the treatment protocols adopted for leukemia and therefore, it was not possible to elucidate how the treatment modified the observed association between BMI and the outcomes.In the included studies, the BMI was categorized into underweight, normal, overweight and obesity using different guidelines.This could have led to heterogeneity in the findings.Although we included studies from a wide geographical location, we were unable to explore the granularity of different protocols used globally.This was mainly due to the wide variation in the protocols used.The value of our analysis would have improved if we could have related the findings with the protocols (and doses of various drugs) employed in the included studies across the various country settings.

Conclusion
Based on the findings of this meta-analysis, we conclude that underweight or obese children with ALL and AML leukemia tend to have an increased risk of poor survival outcomes.Future studies should explore the underlying mechanisms that lead to poor outcomes to identify potential areas of intervention.Studies should also explore the effect of interventions to address undernutrition and obesity in pediatric leukemia patients on the disease outcome.
35; I 2 = 0.0%, N = 11) (S1 Fig).Similarly, we found that for the comparison between overweight and normal BMI children, around 60% of the weight was given to the study by Eissa et al.A sensitivity analysis that excluded this study did not detect difference in the mortality risk in overweight children (HR 1.06, 95% CI: 0.92, 1.23;I 2 = 0.0%, N = 6) (S1 Fig).